A variety of monitoring applications both in government and industry involve remote sensing of optical phenomena. Remote sensors, for example, are used in connection with facilities security, weapons monitoring and astronomical studies. Remote sensing often employs the use of optical sensors similar to those in a television camera to detect optical phenomena such as movement or light emission. The camera generates electrical signal outputs that can then be manipulated and interpreted using well-known technologies ranging from oscilloscopes to digital pixel-based video monitors and computers.
Because of the remote nature of this sensing technology, the optical signals associated with the events being monitored are often weak and difficult to distinguish over background signals. The problem of detection of weak signals is aggravated where monitored events occur infrequently and signal to noise ratio is low. When monitoring a sparse-event scene for transient events with an optical sensor, many different types of false events can create signals that look identical to expected target signals, making the detection problem untenable. Accurate detection of true signals associated with monitored events and, where necessary, avoidance of false alarms due to detection of false signals or noise, requires the ability to reliably differentiate true signals from other true-signal-emulating events.
Noise that can cause confusion in analysis of signal data may be associated with either the detecting apparatus or the environment in which detection takes place. Noise, for example, can result in generation of electrical artifacts that may mistakenly be interpreted by a detection system to represent real events of the type being monitored. Common noise sources are well known and understood by individuals skilled in the art of optical radiation detection, and they include photon noise, Johnson noise, shot noise, generation/recombination, 1/f noise, temperature noise, microphonics and postdetector electronic noise. These noise sources are described in detail in E. L. Dreniak and D. G. Crowe, Optical Radiation Detectors, .COPYRGT. 1984 John Wiley and Sons, Inc., pp. 36-59, which is herein incorporated by reference in its entirety.
An example of a detection scenario in which there exists controversy over whether apparent signals are in fact real is in the field of astrophysics. Studies by a research team led by Dr. Louis A. Frank of the University of Iowa have postulated the existence of thousands of small ice-containing comets constantly bombarding the Earth resulting in tons of water entering the Earth's atmosphere on a daily basis. This theory is based on image data collected from NASA's Polar Visible Imaging System. (See: NASA Press Release 97-112, May 28, 1997.) Disagreement exists in the scientific community over what the data suggest, or even if the data represent actual optical phenomena. Being able to prove whether the signals being interpreted were the result of actual optical phenomena, and not a consequence of noise that is unrelated to monitored physical events, could resolve much of the current controversy.
Some existing technology directed to distinguishing real event signals from false event signals has centered on multiple detection methodologies. In theory, if more than one detector registers a response to a presumed event, the likelihood that it is not real is significantly reduced. It is very unlikely that two or more identical artifacts will occur at the same moment in separate detectors.
Although the theory of multiple detection is sound, in practice, it is difficult to implement. Use of two or more separate focal planes, for example, in focal plane arrays, requires assurance 1) that the separate detectors are, indeed, monitoring the same target, and 2) that signal arrival is either simultaneous or computationally manipulated so as to be legitimately interpreted as simultaneous. The issues can result in a mapping problem that is at best expensive to solve, and at worst is intractable.